AI Der Ring:The Forging of the Future A Wagnerian Gesamtkunstwerk Reimagined through Multi-agent System

ICLR 2026 Conference Submission16698 Authors

Keywords: Multi-Agent Systems; AI-Enhanced Opera; Interactive Performance; Wagnerian Motifs

TL;DR: This paper reimagines Wagner’s *Ring* as a computational Gesamtkunstwerk through the “AI Der Ring” framework, validated via YuLan-WanXiang, showcasing scalable multi-agent creativity in narrative, performance, adaptation, and audience engagement.

Abstract:

This paper presents a comprehensive exploration of how artificial intelligence (AI) reimagines Richard Wagner's Der Ring des Nibelungen as a computational Gesamtkunstwerk. Centered on the “AI Der Ring” framework, we integrate four dimensions of multi-agent system-enhanced operatic creation: multi-agent narrative construction, single-agent multi-role performance, dynamic scene adaptation, and interactive audience engagement. Each component leverages advanced machine intelligence to preserve Wagner’s core philosophical themes while expanding the expressive possibilities of AI-era opera.
To validate this framework, we implemented a multi-agent operatic simulation using YuLan-WanXiang, a next-generation social simulation platform developed by the Gaoling School of Artificial Intelligence at Renmin University of China. Our experiments successfully replicated key aspects of the performance pipeline, confirming the system’s stability, narrative coherence, and audience responsiveness under dynamic and distributed configurations.
Building upon this foundation, we will generate four new multi-agent operas—reinterpretations of Das Rheingold, Die Walküre, Siegfried, and Götterdämmerung—to explore the full operatic cycle through the lens of distributed AI creativity. This initiative not only honors Wagner’s artistic vision but also demonstrates how multi-agent system can serve as a generative co-creator in large-scale performative arts. Our work offers a scalable and experimentally validated methodology for AI-driven cultural production, bridging historical tradition with emergent digital aesthetics.

Primary Area: generative models

Submission Number: 16698